Research On WiFi Fingerprinting Location Technology Based On Mobile Terminal

With the fast development of mobile Internet and the increasing demand for location based services(LBS), indoor location technology develops rapidly. In recent years, WiFi access points(AP) are widely equipped in shopping malls, hospitals and other public places, making WiFi indoor location technology become the important part in indoor location domain. Mobile terminal(such as mobile phone, PDA) based WiFi fingerprinting technology, which has the characteristics of high accuracy, simple implementation and low cost, plays an important role with wide prospect in commercial, social, medical and other aspects.This paper focuses on the mobile terminal based WiFi fingerprinting loaction technology, and deeply studies its complexity, stability and accuracy. The advanced algorithms and methods are considered in detailed.Firstly, the principle of existing fingerprinting location methods is studied, and the main sources of location error are investigated. The research shows that the existing WiFi fingerprinting location methods only use matching relationship between fingerprint and location, and always ignore NLOS(Non Line of Sight) propagation information in indoor situation. Therefore, the NLOS environment based indoor position scheme is proposed, and location is estimated by the fingerprinting method combined with the explored signal attenuation distance model. The proposed scheme is beneficial to reduce the effects of NLOS bias of RSSI on location, for taking NLOS attenuation information as priori knowledge of the location calculation. Simulation results show that the proposed method can improve 25% of location accuracy compared with the traditional WiFi fingerprinting method.Further, the main problems of the existing fingerprinting location methods for multi-floor environment are analyzed, namely the increasing of computational complexity and low accuracy of floor identification. For these two issues, the existing affinity propagation algorithm is applied for fingerprints clustering firstly, which reduces the computational complexity of matching algorithm. Then RSSI threshold based floor identification method is put forward to improve the accuracy of floor identification, according to the signal attenuation characteristics between floors. Simulation results show that the proposed strategy can effectively reduce the computational complexity of the matching algorithm, with higher accuracy of floor identification.Finally, in order to reduce the impact of signal interference on location accuracy and robustness, the inertial sensors assisted WiFi location method is proposed. User’s walking state is analyzed by signals from inertial sensors in terminal, which utilized to optimize accuracy and robustness of WiFi fingerprinting location. The proposed method is implemented on Android platform, and tested through Android phone. Experimental results show that, the proposed method can effectively improve robustness and accuracy comparing to the traditional WiFi fingerprinting method, with location accuracy of 3m.